Data for "Semi-Automated Indoor Geometry Reconstruction for Daylight Simulation"

This repository contains the I/O data for the project <strong>"</strong>Semi-Automated Indoor Geometry Reconstruction for Daylight Simulation<strong>."</strong>Unzip the content of the zip file in the 'evaluation' sub-folder in the code repository (see references) to have the full data-code package.<br><strong>Abstract:</strong>This study presents a semi-automated pipeline for reconstructing indoor geometries from point cloud data for daylight simulation. The pipeline generates watertight models of permanent architectural surfaces with window boundaries through three steps: (1) preprocessing, (2) permanent structure reconstruction, and (3) window boundary extraction. The pipeline was evaluated in four rooms of varying complexity against manually reconstructed models, with daylight availability and glare simulations performed in <em>Radiance</em>. Daylight availability results show absolute errors below 10% for UDI, with mean TAI percentage errors within 18% for rooms with rectangular windows and up to 44% for those with non-rectangular windows. The DGP error remains under 4%, and the modelling time does not exceed 5 minutes in any scenario. The approach enables rapid generation of simulation-ready models with acceptable accuracy for CBDM.

本仓库包含项目《用于采光模拟的半自动化室内几何重建》（Semi-Automated Indoor Geometry Reconstruction for Daylight Simulation）的输入/输出（I/O）数据。请将该压缩包内的内容解压至代码仓库的`evaluation`子文件夹中（详见参考文献），以获取完整的数据-代码套件。

摘要：本研究提出了一种面向采光模拟的半自动化流程，可从点云数据中重建室内几何模型。该流程通过三个步骤生成带有窗边界的永久建筑表面水密模型：（1）预处理；（2）永久结构重建；（3）窗边界提取。本流程针对4个复杂度不同的房间，与手动重建模型开展对比评估，并在Radiance中完成了采光可用度与眩光模拟。采光可用度结果显示，有效日照照度（UDI）的绝对误差低于10%；对于带有矩形窗户的房间，时间平均采光指数（TAI）的百分比平均误差在18%以内，而非矩形窗户的房间则最高达44%。眩光概率（DGP）误差始终低于4%，且所有场景下的建模时长均不超过5分钟。本方法可快速生成满足计算机辅助采光模拟（CBDM）精度要求的可直接用于模拟的模型。